Fixes for dataloader

testing/test_bucket_dataloader.py

@@ -32,7 +32,7 @@ bucket_tolerance = 64
 batch_size = 4
 
 dataset_config = DatasetConfig(
-    folder_path=dataset_folder,
+    dataset_path=dataset_folder,
     resolution=resolution,
     caption_ext='txt',
     default_caption='default',
@@ -48,22 +48,22 @@ for batch in dataloader:
     batch: 'DataLoaderBatchDTO'
     img_batch = batch.tensor
 
-    chunks = torch.chunk(img_batch, batch_size, dim=0)
-    # put them so they are size by side
-    big_img = torch.cat(chunks, dim=3)
-    big_img = big_img.squeeze(0)
-
-    min_val = big_img.min()
-    max_val = big_img.max()
-
-    big_img = (big_img / 2 + 0.5).clamp(0, 1)
-
-    # convert to image
-    img = transforms.ToPILImage()(big_img)
-
-    show_img(img)
-
-    time.sleep(1.0)
+    # chunks = torch.chunk(img_batch, batch_size, dim=0)
+    # # put them so they are size by side
+    # big_img = torch.cat(chunks, dim=3)
+    # big_img = big_img.squeeze(0)
+    #
+    # min_val = big_img.min()
+    # max_val = big_img.max()
+    #
+    # big_img = (big_img / 2 + 0.5).clamp(0, 1)
+    #
+    # # convert to image
+    # img = transforms.ToPILImage()(big_img)
+    #
+    # show_img(img)
+    #
+    # time.sleep(1.0)
 
 cv2.destroyAllWindows()
 

toolkit/dataloader_mixins.py

@@ -251,8 +251,8 @@ class ImageProcessingDTOMixin:
             transform: Union[None, transforms.Compose]
     ):
         # todo make sure this matches
-        img = Image.open(self.path).convert('RGB')
         try:
+            img = Image.open(self.path).convert('RGB')
             img = exif_transpose(img)
         except Exception as e:
             print(f"Error: {e}")